Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mohamednidsaid/pinterest-skill --skill pinterest-analyticsgit clone --depth 1 https://github.com/mohamednidsaid/pinterest-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mohamednidsaid/pinterest-skill/pinterest-analytics)<a href="https://agentmods.dev/skills/mohamednidsaid/pinterest-skill/pinterest-analytics"><img src="https://agentmods.dev/badge/skills/mohamednidsaid/pinterest-skill/pinterest-analytics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mohamednidsaid/pinterest-skill/pinterest-analytics"><img src="https://agentmods.dev/badge/skills/mohamednidsaid/pinterest-skill/pinterest-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00159 | $0.02079 |
| Opus 5 | $0.00079 | $0.01040 |
| Sonnet 5 | $0.00032 | $0.00416 |
| Haiku 4.5 | $0.00016 | $0.00208 |
Grade A, and why
pinterest-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pinterest Analytics
Turn raw Pinterest data (CSVs, PDFs, dashboard screenshots) into insight and client-ready reports.
Why this skill exists
Pinterest data arrives messy and in mixed formats. Clients forward PDF summaries, marketers screenshot the dashboard, and Pinterest's own CSV exports vary in structure depending on which page they were exported from. The goal is always the same: figure out what content is working, how performance is moving over time, and communicate it clearly to someone who won't look at a spreadsheet. Keep that end goal in mind at every step — the deliverable is insight, not a data dump.
Workflow overview
- Ingest every file the user provides (see "Reading each input type")
- Normalize into one tidy dataset (see "Normalizing the data")
- Analyze — top performers, trends, and anything the user specifically asked for
- Report — pick the right deliverable format and build it
Step 1: Reading each input type
Inventory all uploaded files first. Users often upload a mix (e.g., a CSV plus screenshots of charts the CSV doesn't cover). Every file is a data source; don't ignore any.
CSV exports. Read with pandas. Pinterest exports vary; common shapes include:
- Pin-level export: one row per pin with columns like
Pin ID,Pin title,Impressions,Engagements,Pin clicks,Outbound clicks,Saves, sometimesCreated dateandBoard name - Time-series export: one row per day with aggregate metrics (
Date,Impressions,Engagements, ...) - Ads exports: campaign/ad group rows with
Spend,CPC,CTR, conversion columns
Column names shift over time and by locale. Match columns by meaning, not exact name (e.g., "Link clicks" ≈ "Outbound clicks" in older exports). Check for thousands separators, percent signs, and currency symbols stored as text — strip and convert to numeric before doing math.
PDF reports. Consult the pdf-reading skill if available. Extract tables and stated metrics. PDFs from Pinterest or agency tools usually contain summary numbers (period totals, top pins) — capture the reporting period from headers or page text, since the numbers are meaningless without it.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 111 lines · 159 tokens per session scan A 0b4c264e497a
pinterest-analytics is a skill published in the GitHub repository mohamednidsaid/pinterest-skill (4 stars, last pushed 2mo ago), licensed MIT. It adds 159 tokens to every session and 2,079 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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